VERSION 01
Our first attempt at the map demonstrates how important formatting maps can be in communicating information effectively. In this example, the basemap distracts from the other layers and it is hard to distinguish what the map's features represent. The open space polygons are colored blue, which might be confused with water. The commercial parking points are too large and the star shape adds visual complexity, which . The metered parking polygons are almost invisible.
ggplot() +
#TITLE
ggtitle("CAMBRIDGE PARK [ ING ]") +
theme(
plot.title = element_text(
color="black",
size=10,
face="bold", #FONT FACE OPTIONS = PLAIN, BOLD, BOLD.ITALIC, ITALIC
vjust = 5,
hjust = .5))+
#BASE MAP
annotation_map_tile(
zoomin = 0,
progress = "none",
type = "stamenwatercolor",
alpha = .5) +
geom_sf() +
labs(caption = "Map tiles by Stamen Design. Data by OpenStreetMap") +
#DATA
geom_sf(
data = openspace,
color = NA,
alpha = 0.5,
aes(fill = "Open Space")
) +
geom_sf(
data = meters,
color = NA,
shape = NA,
aes(fill = "Metered Parking")
) +
geom_sf(
data = commercialparking,
shape = 11,
size = 5,
fill = NA,
aes(color = "Commercial Parking")
) +
scale_fill_manual(values = c("brown1", "blue"), name = "") +
scale_color_manual(values = "brown1", name = "") +
theme_void()
VERSION 02
This next map uses a high contrast dark theme and increased the dpi output for the R markdown chunk, in hopes of crisper data information. Open space polygons and commercial parking points pop from the page, while the metered parking more subtly suggests denser corridors, where people will pay to park on the street. While the map includes the names of neighborhoods and districts, the words are very faint and almost illegible. While the dark color scheme helps the map features stand out, the base map loses relevance as a map and serves more as a background color.
ggplot() +
ggtitle("Cambridge Park(ing)") +
#BASE MAP
annotation_map_tile(
zoomin = 0,
progress = "none",
type = "cartodark") +
geom_sf() +
labs(caption = "Map tiles and data by OpenStreetMap") +
#DATA
geom_sf(
data = openspace,
color = NA,
alpha = 0.6,
aes(fill = "Open Space")
) +
geom_sf(
data = meters,
fill = "white",
aes(color = "Parking Meters")
) +
geom_sf(
data = commercialparking,
shape = 20,
size = 3,
aes(color = "Commercial Parking")
) +
scale_color_manual(values = c("deeppink", "darkviolet"), name = "") +
scale_fill_manual(values = "chartreuse", name = "") +
theme_void()
VERSION 03
This next map uses a toned-down palette and the faint basemap allows basic geographic features like water areas to show through. In addition, the simple basemap allows the viewer to focus on the point and polygon layers atop it. In this version, we changed the symbology of the metered parking polygons to have just a fill with no outline in order to the true size of the parking spaces, but makes them a bit hard to find.
ggplot() +
ggtitle("Cambridge Park(ing)") +
#BASE MAP
annotation_map_tile(
zoomin = 0,
progress = "none",
type = "cartolight") +
geom_sf() +
labs(caption = "Map tiles by OpenStreetMap; data from City of Cambridge") +
#DATA
geom_sf(
data = openspace,
color = NA,
alpha = 0.5,
aes(fill = "Open Space")
) +
geom_sf(
data = meters,
color = NA,
shape = NA,
aes(fill = "Metered Parking")
) +
geom_sf(
data = commercialparking,
shape = 3,
size = 2,
fill = NA,
aes(color = "Commercial Parking")
) +
scale_fill_manual(values = c("brown3", "forestgreen"), name = "") +
scale_color_manual(values = "brown1", name = "") +
theme_void()